1. Field of the Invention
The present invention relates to a playback apparatus that presents songs suited to the current environmental noise, and to a display method for such a playback apparatus.
2. Description of the Related Art
Certain playback apparatus have become commercially viable in recent years, wherein songs are automatically categorized into various categories, and as a result of the user selecting a particular category, songs corresponding to the selected category are automatically selected and played back. In such playback apparatus, a song categorization method is used wherein characteristic quantities, such as the song tempo and chord progression, are detected for each song, and the songs are then automatically categorized into various categories on the basis of the detected characteristic quantities.
For example, Japanese Unexamined Patent Application Publication No. 2005-274708 discloses a method whereby a song is analyzed, and characteristic quantities, such as the tempo and perceived speed, are detected. As another example, Japanese Unexamined Patent Application Publication No. 2005-275068 discloses a method whereby the signal components of each pitch in an audio signal are analyzed.
Meanwhile, portable playback apparatus able to play songs outside the home and outdoors have also come into widespread use recently. Such portable playback apparatus are also capable of automatically categorizing songs using the song categorization methods described above. For example, a portable playback apparatus may be configured such that when a particular category is selected by the user, the portable playback apparatus plays songs corresponding to the selected category.
However, since such portable playback apparatus can be used in a variety of environments, the environmental noise state may differ depending on surrounding conditions. In other words, the surrounding environmental noise level differs depending on the environment. For this reason, a song category selected by the user may not be suited to the current environmental noise.
In addition, the surrounding environmental noise may change, such as when using a playback apparatus to listen to songs while moving. For this reason, even if a song category suited to the surrounding environmental noise is selected when initially listening to songs, the surrounding environmental noise may change as a result of the user moving, and the selected song category may be unsuited to the current environmental noise at the destination.
In order to solve such problems, a playback apparatus able to automatically select and play songs suited to the environmental noise has been proposed. In such a playback apparatus, characteristic quantities like those described above are respectively extracted for both the environmental noise and the songs, and then particular songs are automatically selected on the basis of the respectively detected characteristic quantities.
FIG. 22 illustrates an exemplary usage of a playback apparatus 101 of the related art. In the example shown in FIG. 22, a microphone 103 (also referred to hereinafter as a mike 103) and headphones 102 are connected to a portable playback apparatus or similar playback apparatus 101, whereby the user is listening to songs recorded onto the playback apparatus 101 via the headphones 102. The mike 103 is built into the headphones 102, for example, and picks up the environmental noise heard at the position of the user's ears when the headphones 102 are worn.
The playback apparatus 101 conducts predetermined analysis of the environmental noise picked up by the mike 103, and extracts characteristic quantities therefrom. In addition, the playback apparatus 101 also conducts predetermined analysis of the songs recorded onto the playback apparatus 101 and extracts characteristic quantities therefrom, using the same characteristic quantity extraction method as that used for the environmental noise. Subsequently, the playback apparatus 101 compares the characteristic quantities of the environmental noise to the characteristic quantities of the songs, and then automatically selects the songs that are easiest to hear given the current environmental noise.
The method for automatically selecting songs suited to the current environmental noise may, for example, involve extracting a plurality of types of characteristic quantities from both the environmental noise and the songs, and then selecting songs on the basis of the extracted characteristic quantities such that the characteristic quantities for both the environmental noise and the songs are mutually similar. For example, FIG. 23 illustrates exemplary categorization results for environmental noise and a song categorized on the basis of two different characteristic quantities respectively extracted from the environmental noise and the song.
As shown in FIG. 23, on the basis of their respective characteristic quantities, the environmental noise and the song are mapped onto a two-dimensional plane defined by two evaluation axes A and B, which represent the two characteristic quantities. In this case, FIG. 23 shows that the categories of the environmental noise and the song have similar characteristics to the degree that the positions (i.e., the distances) between individually mapped categories are near to each other.
As an easily understood practical example, consider that lively rock music is easy to hear in loud environments, and slow classical music is easy to hear in quiet environments. In other words, if the noise and the song are similar, then there is a higher probability that the song will not be masked by the noise, and thus be easy to hear. It can be intuitively understood that slow classical music is hard to hear in loud environments; this is because the characteristic quantities of the noise and the song differ significantly. In contrast, rock music is not particularly hard to hear in quiet environments, and thus a significant difference in the characteristic quantities of noise and song might not result in the song being hard to hear. However, in this case, there is a problem in that sound leakage from the headphones might be a nuisance to surrounding persons.
In other words, if it is assumed that a song category having characteristics similar to those of the current environmental noise is easy to hear given such noise, then the song categories that are close to the mapped position of the current environmental noise are easy-to-hear song categories. Consequently, if the current environmental noise is categorized into “Category b”, for example, then song categories categorized into “Category 2” are selected from among the song categories mapped into the categories from “Category 1” to “Category 7”, since “Category 2” is mapped to the position closest to the position of “Category b”.
It should be appreciated that song categories having characteristics similar to those of particular environmental noise are not limited to being easy-to-hear song categories given such noise. The correspondence between noise and song as well as the selection method may also be changed, depending on the types of characteristic quantities used as the evaluation axes. However, in order to simplify explanation, song categories having characteristics similar to those of the current environmental noise are herein described as being song categories that are easy to hear given such environmental noise.
A process flow for a song selection method of the related art will now be summarized with reference to the flowchart shown in FIG. 24. In step S101, the playback apparatus 101 is powered on. If instructions to play songs according to the surrounding environmental noise are issued in step S102, then in step S103, it is determined whether or not characteristic quantities have been extracted for all songs recorded onto the playback apparatus 101. If it is determined that characteristic quantities have not been extracted for all songs, then the process transitions to step S104, and a song for characteristic quantity extraction is selected. In contrast, if it is determined that characteristic quantities have been extracted for all songs, then the process transitions to step S107.
In step S105, the characteristic quantities of the selected song are extracted. In step S106, it is determined whether or not characteristic quantities have been extracted for all songs targeted for characteristic quantity extraction. If it is determined that characteristic quantities have been extracted for all songs, then the process transitions to step S107. In contrast, if it is determined that characteristic quantities have not been extracted for all songs targeted for characteristic quantity extraction, then the process transitions to step S104, and another song is selected for characteristic quantity extraction.
Next, in step S107, environmental noise is picked up via the mike 103, and in step S108, the characteristic quantities of the environmental noise thus picked up are extracted. In step S109, the characteristic quantities of the environmental noise are compared to the characteristic quantities of the songs. Subsequently, the song category having characteristic quantities closest to those of the environmental noise is selected as the easy-to-hear song category given the current environmental noise, and songs categorized into the selected song category are then played back.
In step S110, it is determined whether or not to continue music playback. If it is determined that music playback is to be continued, then the process returns to step S107, and environmental noise pickup is again conducted via the mike 103. In contrast, if it is determined that music playback is not to be continued, then the process transitions to step S111, the playback apparatus 101 is powered off by the user, and the above series of processes is terminated.
In this way, a playback apparatus 101 of the related art is configured to extract characteristic quantities from both environmental noise and songs, and on the basis of the respectively extracted characteristic quantities, automatically select and play back songs that are easy to hear given the current environmental noise.